AI Video Upscalers and Frame Interpolation

Wan2GP brings video, image, music and speech generation to your own computer, with particular attention to GPUs with limited memory. It's for creators who want several media models in one browser interface. The project builds on Wan-Video/Wan2.1.

SD.Next is a self-hosted web interface for artists, researchers and people who want to generate and edit images or videos on their own hardware. It builds on Automatic1111 WebUI's original codebase and supports Stable Diffusion alongside other diffusion models. It's open source under Apache 2.0.

FaceFusion is an AI face manipulation tool for photos and videos that processes media on your own machine. It's aimed at content creators, VFX artists, and film studios that want control over their footage and personal data. Local processing keeps that media on your hardware rather than sending it to a cloud service.

Waifu2x-Extension-GUI is a local AI upscaler for Windows users working with anime, photos and video. It combines image enlargement, noise reduction and video frame interpolation in a desktop interface. Media processing stays on your PC; the app doesn't upload your files or collect user data.

Flowframes is a Windows desktop app that uses local AI to generate intermediate frames for smoother video and animation. It's for people working with camera footage, 2D animation or rendered video who want a graphical interface for interpolation. The app is open source under GPL-3.0 and available as donationware, with free builds.

Amuse combines AI generation with media editing in a Windows app that runs models on your own hardware. It's for people who want to create images, video, audio and text locally, then work on the results in the same application. Its editor also accepts existing local video.

CodeFormer restores degraded faces in photos and videos using a learned library of facial details and a Transformer model. It's for people restoring images on their own hardware, developers adding face enhancement to a project, and researchers working on image restoration. Its main distinction is an adjustable balance between visual quality and fidelity to the input face.

Real-ESRGAN is a local AI upscaler and restoration toolkit for people enlarging images or improving video, with dedicated models for anime illustrations and animation. It builds on ESRGAN and uses models trained entirely on synthetic data to address degraded images. The code is open source under the BSD 3-Clause license.

Practical-RIFE is a local AI frame interpolation tool for engineers and developers working with video. It generates intermediate frames to increase frame rates, with models intended for ordinary footage, animation, and post-processing videos made by diffusion models. The Python project builds on RIFE and SAFA, with an emphasis on how the output looks rather than improvements in numerical image-quality scores alone.

chaiNNer is a desktop image processing editor for people who want AI upscaling and repeatable editing workflows without writing scripts. It runs models locally on Windows, macOS, and Linux. Connected nodes let you combine model processing with ordinary image edits in the same workflow.

Video2X runs AI video upscaling and frame interpolation on your own hardware. It's for people who want to increase a video's resolution or generate extra frames for smoother motion, including those working with anime footage. The project is open source under AGPL-3.0.